code: def convert_predictions(
      predictions,
      output_features,
      return_type="dict",
      backend: Optional["Backend"] = None,  # noqa: F821
  ):
      convert_fn = get_from_registry(return_type, conversion_registry)
      return convert_fn(predictions, output_features, backend)
  
file_path: ludwig/ludwig/data/postprocessing.py
imports: import os
  from typing import Any, Dict, List, Optional, Union
  import numpy
  import pandas
  import torch
  from ludwig.backend import LOCAL_BACKEND
  from ludwig.data.utils import convert_to_dict
  from ludwig.utils.data_utils import DATAFRAME_FORMATS, DICT_FORMATS
  from ludwig.utils.dataframe_utils import to_numpy_dataset
  from ludwig.utils.fs_utils import has_remote_protocol, open_file
  from ludwig.utils.misc_utils import get_from_registry
  from ludwig.utils.strings_utils import make_safe_filename
  from ludwig.utils.types import DataFrame
label_desc: Use image node_id 4 for calling a global function with example usage: convert_predictions(predictions, output_features, return_type, backend) and returns: convert_fn